This invention relates to image processing and, more particularly, to a process of transforming images to achieve desirable final prints. A major objective of the present invention is to reduce the number of pre-press process iterations and the concomitant degradation of image data.
In image processing, computer data is either converted directly into color negative or positive images or indirectly into color images through a secondary printing process. Direct color imaging includes photographic color imaging, dye sublimation printing, ink jet printing, electrostatic printing and bubble jet printing. Indirect printing includes color offset printing and gravure.
In many direct applications such as conventional gravure and offset printing, a printing plate must be created for each color. The most common way of creating a printing plate is through photographic contact printing using film negatives or positives. In a color offset process the color is created by printing several colored, monochromatic images ("color separations") on top of one another. If transparent ink is used, the overlaying of the different color layers can produce a full-color image. The most common combination of color layers is cyan, magenta, yellow and black, which enables the printer to reproduce visually acceptable full-color images. In a direct method such as ink jet printing, different color layers are applied directly to a substrate. Whether an image is created directly or indirectly, the color separations are frequently created electronically.
It is difficult even for an experienced color separationist to look at an image and set up processing parameters. Because people perceive color comparatively, changing one range of colors in an image can have unintended side effects on the perception of the other ranges of colors in the image. Such complexities often cause a color separationist to misread an image. Often the image must be approved by someone other than the person who performs the on-screen color corrections. In a typical case, the customer has a good idea of the final image he wants, and depends on the image processing service to achieve it. On the other hand, the image processing service would know how to achieve the desired effects if they could be adequately communicated. Since image perception, and especially color perception, is subjective, communication about the desired final image is very difficult. In such a case, a candidate image typically must be printed and sent or shown to the customer for approval. Often the image must be discussed, modified, and reprinted several times before satisfactory colors are achieved. On average, pre-press color separations are redone three times before approval. Because of the communication difficulty and the tremendous range of possible transformations, a customer will often have to travel to a processing house to help with the color separation on-site, at significant cost of money and time.
Moreover, each iteration typically results in irremediable data loss in the conversion from higher precision data to lower. For this reason, images are frequently rescanned, and each iteration adds further to the expense. Typically, a tremendous amount of data is lost between acquisition and output. Most professional quality scanners acquire data at 12 or 16 bits per picture element (pixel) in each color channel, apply electronic image processing to the image, and then map the resulting data to the industry-standard 8 bits per pixel in each color channel at the time it is sent to the computer for storage or to the output scanner for imaging. Each transformation can result in new data loss. For example, if four 8-bit transformations are added, the result is 10 bit data. When this data is re-stored at 8 bits, further data is lost.
An 8-bit-per-channel image breaks down the color data for each of three channels into 256 steps, resulting in 1.68 E+07 possible values. The original 12- or 16-bit-per-channel images contain much more information: A 12-bit-per-channel image contains 4,096 times as many color values as an 8-bit-per-channel image (data is broken into 4,096 steps resulting in 6.87 E+10 possible color values). Similarly, a 16-bit-per-channel image contains 16,777,216 times as many colors as an 8-bit-per-channel image (65,536 steps resulting in 2.81 E+14 color values).
Applying color corrections to data causes irreversible data loss and loss of detail in some portion of the dynamic range of the image. In typical systems, the 8-bit-per channel image is called up on the color separationist's computer monitor, and transformations are performed on that image. When color corrections are applied to low-precision data, such as those in an 8-bit-per-channel image, the relative data loss is greater.
The sequential nature of the color-correction process can also cause the transformations to get channeled into unfortunate directions. An earlier transformation may lead the user to a later transformation that he or she would not otherwise have chosen, in order to harmonize with earlier choices. Furthermore, color correction based on an on-screen display is typically inadequate. Often the user is required to choose sequential transformations from an on-screen display that looks very different from what the printed image will look like. Colors on a glowing monitor do not look like colors on a printed page. Ambient light can wash out the colors on a monitor. To counteract this effect, a user often will darken the room or shroud his monitor and allow his eye to dark-adapt before attempting to edit colors on-screen, but this solution is imperfect at best.
To overcome some of these difficulties, some systems require the user to resort to comparisons between the image he is processing and a standard "reference image" in an attempt to get desired colors. The reference image is a standard image for which sometimes bizarre-appearing screen colors have been mapped to result in acceptable print colors. In theory, if colors in the printed reference image would be acceptable to the user, he can obtain those colors by matching his colors on screen with the screen version of the reference image. However, in practice the reference image is a very limited tool. The user often must compare very dissimilar images, such as an image of two people with an image of a country cottage. It is difficult to predict desirable results with comparisons of such dissimilar images. In any case, the reference image is often a very poor predictor of what the image will look like when printed. Ambient light can wash out the colors in the reference image, making comparison problematic.
What is needed is a color transformation process that allows a user to systematically consider useful candidate transformations from among the billions of possible transformations, and without the necessity of traveling to the pre-press location to aid in color correction. Preferably, the process would enable an acceptable color image to be obtained without expensive and time-consuming iterations of color separations and proofs.